An improved artificial bee colony algorithm with history best points
chinese control and decision conference(2018)
摘要
Depending on the power global search ability, artificial bee colony algorithm attracts more attentions in recent years. But its slow convergence rate constraints its development. To better balance its exploration and exploitation abilities, we define a new point named as mean history best points (MHB) to lead the direction of bee population. The numerical experiments on the basic benchmark functions validate the efficiency of our algorithm.
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关键词
Artificial bee colony,convergence rate,evolutionary computation,global search ability
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